Add a cell for displaying loaded validation results.

PiperOrigin-RevId: 686939867

analysis.ipynb

@@ -312,6 +312,35 @@
     "roc_auc_estimate = call_density.estimate_roc_auc(validation_examples)\n",
     "print(f'Estimated ROC-AUC : {roc_auc_estimate:5.4f}')"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {
+    "id": "0ii9H72iQknv"
+   },
+   "outputs": [],
+   "source": [
+    "#@title Display Logged Validation Examples. { vertical-output: true }\n",
+    "\n",
+    "validation_results = search.TopKSearchResults(top_k=len(validation_examples))\n",
+    "for v in validation_examples:\n",
+    "  validation_results.update(v.to_search_result(\n",
+    "      target_class, project_state.embedding_model.sample_rate))\n",
+    "\n",
+    "samples_per_page = 40  #@param\n",
+    "page_state = display.PageState(\n",
+    "    np.ceil(combined_results.top_k / samples_per_page))\n",
+    "\n",
+    "display.display_paged_results(\n",
+    "    validation_results,\n",
+    "    page_state, samples_per_page,\n",
+    "    project_state=project_state,\n",
+    "    embedding_sample_rate=project_state.embedding_model.sample_rate,\n",
+    "    exclusive_labels=True,\n",
+    "    checkbox_labels=[target_class, f'not {target_class}', 'unsure'],\n",
+    ")"
+   ]
   }
  ],
  "metadata": {

chirp/inference/call_density.py

@@ -21,6 +21,7 @@
 
 from chirp.inference.search import search
 from etils import epath
+import ipywidgets
 import numpy as np
 import pandas as pd
 import scipy
@@ -59,6 +60,29 @@ def to_row(self):
         self.bin_weight,
     ]
 
+  def to_search_result(self, target_class: str, embedding_sample_rate: int):
+    """Convert to a search result for display only."""
+    result = search.SearchResult(
+        filename=self.filename,
+        timestamp_offset=int(embedding_sample_rate * self.timestamp_offset),
+        score=self.score,
+        sort_score=np.random.uniform(),
+        embedding=np.zeros(shape=(0,), dtype=np.float32),
+    )
+    b = ipywidgets.RadioButtons(
+        options=[target_class, f'not {target_class}', 'unsure']
+    )
+    if self.is_pos == 1:
+      b.value = target_class
+    elif self.is_pos == -1:
+      b.value = f'not {target_class}'
+    elif self.is_pos == 0:
+      b.value = 'unsure'
+    else:
+      raise ValueError(f'unexpected value ({self.is_pos})')
+    result.label_widgets = [b]
+    return result
+
   @classmethod
   def from_search_result(
       cls,